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In this study, a full vehicle with advanced LMS comfort and durability tire (CDT) model was established with ADAMS software to predict the spindle loads of the vehicle under a severe proving ground rough road event. From a series of simulations with various design changes, the spindle loads sensitivities to those design changes were identified. The simulated results were also compared with the measured data and a good correlation was achieved.

In this study, a full vehicle with durability tire model established with ADAMS is applied to simulate the dynamic behavior of the vehicle under severe rough road proving ground events, where the shock force-velocity characteristics are modeled as nonlinear curves and multi-stage representations, respectively. The shock forces and velocities at each corner are resolved and through full factorial DOE, the shock forces and velocities response surface models are established to analyze the sensitivities of shock force and velocity to the shock damping characteristics.

In this study, two common types of suspension are used to study back-calculated spindle loads sensitivity to the availability of suspension component loads, under a severe loading proving ground event. The previously back-calculated spindle loads (Targets) are initially used as the inputs to resolve suspension component loads, which are considered as the “perfectly measured data”. With full factorial design of experiments (DOE), the back-calculated spindle loads using the known suspension component loads are then compared with the targets to produce the sensitivity of the spindle loads in comparison with the suspension components.

In this paper, cradle design functional objectives are briefly reviewed and a durability development process is proposed focusing on the cradle loads, stress, strain, and fatigue life analysis. Based upon the proposed design process, sample isolated and non-isolated cradle finite element (FE) models for a uni-body sport utility vehicle (SUV) under different design phases are solved and correlated with laboratory bench and proving ground tests. The correlation results show that the applied cradle models can be used to accurately predict the critical stress spots and fatigue life under various loading conditions.